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$LOAD_PATH.unshift "./lib"
require 'benchmark'
require 'rspec/expectations'
require 'securerandom'
extend RSpec::Matchers
sizes = [10, 100, 1000, 2000, 4000]
puts "rspec-expectations #{RSpec::Expectations::Version::STRING} -- #{RUBY_ENGINE}/#{RUBY_VERSION}"
puts
puts "Passing `match_array` expectation with lists of distinct strings"
puts
Benchmark.benchmark do |bm|
sizes.each do |size|
actual = Array.new(size) { SecureRandom.uuid }
expecteds = Array.new(3) { actual.shuffle }
expecteds.each do |expected|
bm.report("#{size.to_s.rjust(5)} items") do
expect(actual).to match_array(expected)
end
end
end
end
__END__
Before new composable matchers algo:
10 items 0.000000 0.000000 0.000000 ( 0.000857)
10 items 0.000000 0.000000 0.000000 ( 0.000029)
10 items 0.000000 0.000000 0.000000 ( 0.000018)
100 items 0.000000 0.000000 0.000000 ( 0.000334)
100 items 0.000000 0.000000 0.000000 ( 0.000372)
100 items 0.000000 0.000000 0.000000 ( 0.000331)
1000 items 0.030000 0.000000 0.030000 ( 0.029778)
1000 items 0.030000 0.000000 0.030000 ( 0.030566)
1000 items 0.030000 0.000000 0.030000 ( 0.033150)
2000 items 0.140000 0.000000 0.140000 ( 0.141719)
2000 items 0.120000 0.000000 0.120000 ( 0.124348)
2000 items 0.120000 0.000000 0.120000 ( 0.121202)
4000 items 0.490000 0.000000 0.490000 ( 0.500631)
4000 items 0.470000 0.000000 0.470000 ( 0.468477)
4000 items 0.490000 0.010000 0.500000 ( 0.492957)
After:
10 items 0.000000 0.000000 0.000000 ( 0.001165)
10 items 0.000000 0.000000 0.000000 ( 0.000131)
10 items 0.000000 0.000000 0.000000 ( 0.000127)
100 items 0.000000 0.000000 0.000000 ( 0.005636)
100 items 0.010000 0.000000 0.010000 ( 0.004881)
100 items 0.000000 0.000000 0.000000 ( 0.004676)
1000 items 0.500000 0.000000 0.500000 ( 0.505676)
1000 items 0.490000 0.000000 0.490000 ( 0.483469)
1000 items 0.490000 0.000000 0.490000 ( 0.497841)
2000 items 1.950000 0.000000 1.950000 ( 1.966324)
2000 items 1.970000 0.000000 1.970000 ( 1.975567)
2000 items 1.900000 0.000000 1.900000 ( 1.902315)
4000 items 7.650000 0.010000 7.660000 ( 7.672907)
4000 items 7.720000 0.010000 7.730000 ( 7.735615)
4000 items 7.730000 0.000000 7.730000 ( 7.756837)
With "smaller subproblem" optimization: (about 20% slower)
10 items 0.000000 0.000000 0.000000 ( 0.001099)
10 items 0.000000 0.000000 0.000000 ( 0.000110)
10 items 0.000000 0.000000 0.000000 ( 0.000102)
100 items 0.010000 0.000000 0.010000 ( 0.005462)
100 items 0.010000 0.000000 0.010000 ( 0.005433)
100 items 0.000000 0.000000 0.000000 ( 0.005409)
1000 items 0.570000 0.000000 0.570000 ( 0.569302)
1000 items 0.570000 0.000000 0.570000 ( 0.577496)
1000 items 0.560000 0.000000 0.560000 ( 0.555496)
2000 items 2.330000 0.000000 2.330000 ( 2.325537)
2000 items 2.450000 0.000000 2.450000 ( 2.464415)
2000 items 2.470000 0.000000 2.470000 ( 2.472999)
4000 items 9.380000 0.010000 9.390000 ( 9.406678)
4000 items 9.320000 0.010000 9.330000 ( 9.340727)
4000 items 9.330000 0.010000 9.340000 ( 9.358326)
With "implement `values_match?` ourselves" optimization: (about twice as fast!)
10 items 0.000000 0.000000 0.000000 ( 0.001113)
10 items 0.000000 0.000000 0.000000 ( 0.000074)
10 items 0.000000 0.000000 0.000000 ( 0.000071)
100 items 0.000000 0.000000 0.000000 ( 0.002558)
100 items 0.010000 0.000000 0.010000 ( 0.002528)
100 items 0.000000 0.000000 0.000000 ( 0.002555)
1000 items 0.300000 0.000000 0.300000 ( 0.306318)
1000 items 0.260000 0.000000 0.260000 ( 0.253526)
1000 items 0.240000 0.000000 0.240000 ( 0.246096)
2000 items 1.070000 0.000000 1.070000 ( 1.065989)
2000 items 1.040000 0.000000 1.040000 ( 1.047495)
2000 items 1.080000 0.000000 1.080000 ( 1.078392)
4000 items 4.520000 0.000000 4.520000 ( 4.529568)
4000 items 4.570000 0.010000 4.580000 ( 4.597785)
4000 items 5.030000 0.010000 5.040000 ( 5.079452)
With `match_when_sorted?` optimization: (many orders of magnitude faster!)
10 items 0.010000 0.000000 0.010000 ( 0.002044)
10 items 0.000000 0.000000 0.000000 ( 0.000038)
10 items 0.000000 0.000000 0.000000 ( 0.000031)
100 items 0.000000 0.000000 0.000000 ( 0.000149)
100 items 0.000000 0.000000 0.000000 ( 0.000137)
100 items 0.000000 0.000000 0.000000 ( 0.000136)
1000 items 0.000000 0.000000 0.000000 ( 0.001426)
1000 items 0.000000 0.000000 0.000000 ( 0.001369)
1000 items 0.000000 0.000000 0.000000 ( 0.001355)
2000 items 0.010000 0.000000 0.010000 ( 0.003304)
2000 items 0.000000 0.000000 0.000000 ( 0.002192)
2000 items 0.000000 0.000000 0.000000 ( 0.002849)
4000 items 0.000000 0.000000 0.000000 ( 0.007730)
4000 items 0.010000 0.000000 0.010000 ( 0.006074)
4000 items 0.010000 0.000000 0.010000 ( 0.006514)
With e === a || a == e || values_match?(e,a)
10 items 0.000000 0.000000 0.000000 ( 0.002202)
10 items 0.000000 0.000000 0.000000 ( 0.000054)
10 items 0.000000 0.000000 0.000000 ( 0.000046)
100 items 0.000000 0.000000 0.000000 ( 0.000203)
100 items 0.000000 0.000000 0.000000 ( 0.000199)
100 items 0.000000 0.000000 0.000000 ( 0.000192)
1000 items 0.010000 0.000000 0.010000 ( 0.001438)
1000 items 0.000000 0.000000 0.000000 ( 0.001419)
1000 items 0.000000 0.000000 0.000000 ( 0.001474)
2000 items 0.010000 0.000000 0.010000 ( 0.003341)
2000 items 0.000000 0.000000 0.000000 ( 0.003224)
2000 items 0.000000 0.000000 0.000000 ( 0.003251)
4000 items 0.010000 0.000000 0.010000 ( 0.007156)
4000 items 0.010000 0.000000 0.010000 ( 0.006715)
4000 items 0.000000 0.000000 0.000000 ( 0.006676)
With values_match?(e,a)
10 items 0.000000 0.000000 0.000000 ( 0.001173)
10 items 0.000000 0.000000 0.000000 ( 0.000051)
10 items 0.000000 0.000000 0.000000 ( 0.000026)
100 items 0.000000 0.000000 0.000000 ( 0.000171)
100 items 0.000000 0.000000 0.000000 ( 0.000138)
100 items 0.000000 0.000000 0.000000 ( 0.000136)
1000 items 0.010000 0.000000 0.010000 ( 0.001506)
1000 items 0.000000 0.000000 0.000000 ( 0.001486)
1000 items 0.000000 0.000000 0.000000 ( 0.001510)
2000 items 0.010000 0.000000 0.010000 ( 0.003153)
2000 items 0.000000 0.010000 0.010000 ( 0.003883)
2000 items 0.000000 0.000000 0.000000 ( 0.003199)
4000 items 0.010000 0.000000 0.010000 ( 0.007178)
4000 items 0.000000 0.000000 0.000000 ( 0.006629)
4000 items 0.010000 0.000000 0.010000 ( 0.006435)
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